M <- event customer eats mus
K <- event customer eats ketchup
M ^ K <- event customer eats both (where ^ means intersect)
M' <- not M (ie., customer doesn't eat mus )
K' <- not K (ie., customer doesn't eat ketchup)
1) Don't know WTF a contingency table is.
2)
Pr(M) = 375/500 = 0.75
Therefore, Pr(M') = 1-Pr(M) = 1 - 0.75 = 0.25
3)
Pr(K) = 400/500 = 0.80
Therefore, Pr(K') = 1-Pr(K) = 1-0.80 = 0.20
4) Pr(M' ^ K') = Pr (not (M U K)) = 1 - Pr(M U K) where U means union
Pr(M ^ K) = 325/500 = 0.65
Pr(M U K) = Pr(M) + Pr(K) - Pr(M ^ K) = 0.75 + 0.80 - 0.65 = 0.9
Therefore,
Pr(M' ^ K') = 1 - Pr(M U K) = 1 - 0.9 = 0.1
5) Pr(M' U K') = Pr (not(M ^ K)) = 1 - Pr(M^K) = 1 - 0.65 = 0.35
6) Pr(K' | M') = Pr (K' ^ M') / P(M') = Pr (M' ^ K') / Pr(M') = 0.1/0.25 = 0.4
7) Pr(M ^ K) = 0.65
Pr(M) * Pr(K) = 0.80 * 0.75 = 0.6
Therefore, Pr (M ^ K) is not equal to Pr(M)*Pr(K), so ketchup and mus aren't statistically independent.
8) Pr(M^K) = 0.65 is not equal to 0, so ketchup and mus are not mutually exclusive.
Give my handjob to midge.

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, now if that were a test I'd have gotten 0/4. Don't listen to me TSA,
